Authors:
Thorsten Ropertz
;
Patrick Wolf
and
Karsten Berns
Affiliation:
University of Kaiserslautern, Germany
Keyword(s):
Behavior-based Control, Quality-based Perception, Localization, Off-road Robotics.
Related
Ontology
Subjects/Areas/Topics:
Adaptive Signal Processing and Control
;
Informatics in Control, Automation and Robotics
;
Sensors Fusion
;
Signal Processing, Sensors, Systems Modeling and Control
Abstract:
Autonomous navigation in unstructured environments is a challenging task for which behavior-based control systems proved to be suitable due to their inherent robustness against unforeseen situations. But especially the robust perception is still an unsolved problem leading to severe system failures. This paper faces the perception problem by introducing a new data quality-based perception module based on the integrated Behavior-Based Control (iB2C) architecture. Therefore, a new concept of data quality in behavior-based systems and methods for quality-based data fusion are developed while taking advantage of the modularity, extensibility and traceability of the existing architecture. To demonstrate its capabilities, a perception network for robot localization is derived and its outcomes are compared to an state of the art localization filter in simulation and in a real world scenario as well.